An Introduction to Statistical Problem Solving in Geography, Third Edition

Now in its third edition, this highly regarded text has firmly established itself as the definitive introduction to geographical statistics. Assuming no reader background in statistics, the authors lay out the proper role of statistical analysis and methods in human and physical geography. They delve into the calculation of descriptive summaries and graphics, the use of inferential statistics as exploratory and descriptive tools, ANOVA and Kruskal-Wallis tests and different spatial statistics to explore geographic patterns, inferential spatial statistics, and spatial autocorrelation and variograms.

The authors maintain an exploratory and investigative approach throughout, providing readers with real-world geographic issues and more than 50 map examples. Concepts are explained clearly and narratively without oversimplification. Each chapter concludes with a list of major goals and objectives. An epilogue offers over 150 geographic situations, inviting students to apply their new statistical skills to solve problems currently affecting our world. The accompanying CD provides data sets for many of the book's examples, appropriate for use with a variety of statistical and GIS software.

"Rather than dreading statistics, this book shows students the value of a multitude of techniques and how to select the best one for a particular problem. Equally important, the authors show students how to interpret the results of their analysis." --The Pennsylvania Geographer

"It's a great book, especially for geography students who do not have much background in stats. Detailed text description is very useful for students to understand some of the complicated stats concepts." --Daoqin Tong, University of Arizona

"This easy-to-understand book is a great resource for students. It is full of practical examples in plain English. The authors have presented and explained otherwise complicated topics of statistic in a manner that any college student can easily comprehend." --Bhuiyan Alam, University of Toledo